Hypotensive transfusion reactions can occur with blood products that are leukoreduced before storage
Bibliographic record
Abstract
BACKGROUND: Leukoreduction before storage, rather than bedside white blood cell filtration, is recommended to prevent hypotensive transfusion reactions. STUDY DESIGN AND METHODS: Investigation of hypotensive transfusion reactions during radical prostatectomy in two patients on angiotensin-converting enzyme inhibitors. In Patient A, hypotension occurred during the transfusion of each of the following blood products: 2 units of autologous blood deposited and leukoreduced (LR) before storage; 3 units of allogeneic red cells LR before storage; and 2 units of non-LR acute normovolemic hemodilution (ANH) whole blood. When each of the transfusions was stopped, the blood pressure recovered. In Patient B, hypotension occurred during the transfusion of non-LR ANH whole blood. All implicated units were administered rapidly using a blood infuser at 37 degrees C. Bradykinin (BK) and des-Arg9-BK formation and degradation and the activity of kinin-degrading metallopeptidases were measured in plasma samples from both patients. RESULTS: Degradation of des-Arg9-BK was severely impaired and the activity of aminopeptidase P severely reduced in Patient A, but not in Patient B. BK degradation was mildly impaired in both patients. CONCLUSION: Hypotensive reactions can occur with blood products that are LR before storage and non-LR ANH. An inherent defect in the metabolism of kinins may be a risk factor for the development of hypotensive transfusion reactions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".